Defining the learning curve of robotic portal segmentectomy in small pulmonary lesions: a prospective observational study.

Journal: Journal of robotic surgery
Published Date:

Abstract

Although robotic segmentectomy has been applied for the treatment of small pulmonary lesions for many years, studies on the learning curve of robotic segmentectomy are quite limited. Thus, we aim to investigate the learning curve of robotic portal segmentectomy with 4 arms (RPS-4) using prospectively collected data in patients with small pulmonary lesions. One hundred consecutive patients with small pulmonary lesions who underwent RPS-4 between June 2018 and April 2021 were included in the study. Da Vinci Si/Xi systems were used to perform RPS-4. The mean operative time, console time, and docking time for the entire cohort were 119.2 ± 41.6, 85.0 ± 39.6, and 6.6 ± 2.8 min, respectively. The learning curve of RPS-4 can be divided into three different phases: 1-37 cases (learning phase), 38-78 cases (plateau phase), and > 78 cases (mastery phase). Moreover, 64 cases were required to ensure acceptable surgical outcomes. The total operative time (P < 0.001), console time (P < 0.001), blood loss (P < 0.001), and chest tube duration (P = 0.014) were reduced as experience increased. In conclusion, the learning curve of RPS-4 could be divided into three phases. 37 cases were required to pass the learning phase, and 78 cases were needed to truly master this technique.

Authors

  • Mu-Zi Yang
    Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.
  • Zi-Hui Tan
    Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.
  • Abbas E Abbas
    Division of Thoracic Surgery, Department of Thoracic Medicine and Surgery, Lewis Katz School of Medicine at Temple University, Philadelphia, Pa. Electronic address: abbas.abbas@temple.edu.
  • Ji-Bin Li
    Department of Clinical Research, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
  • Chu-Long Xie
    Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.
  • Hao Long
    Department of Urology, The Affiliated Hospital of Southwest Medical University, Luzhou, China.
  • Lan-Jun Zhang
    Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.
  • Jian-Hua Fu
    Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China.
  • Peng Lin
    Zhejiang Key Laboratory of Excited-State Energy Conversion and Energy Storage, Department of Chemistry, Zhejiang University, Hangzhou 310058, China.
  • Hao-Xian Yang
    Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China. yanghx@sysucc.org.cn.